similar to: sprintf("%d", integer(0)) aborts

Hi, I'm very sorry if those questions are repeated over and over, but I cannot find a solution on the net. I try to use speex to encode/decode voice to send over the network. My doubts are: 1. The Bits_Per_Sample I use, are independent from the speex encoding/decoding? (So...can I use 8, 16, 24..and so on?) 2. If I have this situation: SAMPLE RATE.....: 8000 BITS PER SAMPLE.: 16

R community, As you may know, R's iconv doesn't work well converting to and from encodings that allow embedded nulls. For example > iconv("foo", to="UTF-16") Error in iconv("foo", to = "UTF-16") : embedded nul in string: '\xff\xfef\0o\0o\0' However, I don't believe embedded nulls are at issue here, but rather that R's iconv

Hello, JIT compiler interferes with internal R completions: compiler::enableJIT(2) utils:::functionArgs("density", '') gives: utils:::functionArgs("density", '') Note: no visible global function definition for 'bw.nrd0' Note: no visible global function definition for 'bw.nrd' Note: no visible global function definition for 'bw.ucv'

I initially sent this to the biocore mailing list - but it was suggested that r-devel would also find it interesting. Many of us use a macro like #define CALL_DEF(fname, nargs) { #fname, (DL_FUNC)&fname, nargs} for use in function registration for use with .Call. For example, using the example from R Extension manual, if we want to register a C function myCall with three arguments, we

(Sorry for the cross-post--- I wasn't sure which list is more appropriate...) Hi everyone, I've run into segfaults when using my randomForest package on large dataset (e.g., 100 x 15200) and large number of trees (e.g., ntree=7000 and mtry=3000). I'm wondering if anyone can give me some hints on where to look for the problem. The randomForest package mainly consists of two things:

(Sorry for the cross-post--- I wasn't sure which list is more appropriate...) Hi everyone, I've run into segfaults when using my randomForest package on large dataset (e.g., 100 x 15200) and large number of trees (e.g., ntree=7000 and mtry=3000). I'm wondering if anyone can give me some hints on where to look for the problem. The randomForest package mainly consists of two things:

I am writing a function to work with class I am defining. I have a question about using nargs() inside of parentheses function. nargs() shows the same for supplying 1 argument, or no arguments at all. Here is a small example: > "[.myclass"<-function(x,...) print(nargs()-1) > x<-c(1,2,3) > class(x)<-"myclass" > x[] [1] 1 > x[1] [1] 1 > x[1,2] [1] 2

Dear R-devel, Last week I got several responses to my question about debugging segfaults in my code (original post below). After I changed the S_alloc() calls to Calloc()/Free(), the symptom was gone, but I was told to keep looking. So I did: o Switched to Calloc/Free. Electric Fence did not find any problem. o Put assert(index < bound); assert(index >=0); everywhere in the C routine

Hi, is there an easy, robust, and/or recommended way to distinguish a missing argument from an empty argument as in: foo <- function(i, j){ print(missing(j)) print(nargs()) } foo(i) # TRUE, 1 foo(i,) # TRUE, 2 I know I can work around with nargs, the list of arguments and the names of the passed arguments, but I wish there is something already in place for this. This is

Hello everybody, I've run into some strange behavior with memory sanitizer that I can't explain and hope somebody with more knowledge of the implementation would be able to help me out or at least point me into the right direction. For background, I'm using memory sanitizer to check Julia (julialang.org), which uses (or at least will once I track down a few bugs) MCJIT for the code

I assume there are transitions between JITted code and native helper functions. How are you handling them? Are native functions MSan-instrumented? MSan is passing shadow across function calls in TLS slots. Does your TLS implementation guarantee that accesses to __msan_param_tls from JITted and from native code map to the same memory? On Mon, Jan 27, 2014 at 11:36 PM, Evgeniy Stepanov

Il 14/04/2010 14:37, Randy Yates wrote: > > Usually a buffer is one frame of data, and a frame is 20 milliseconds. > Since the sample rate is typically 8 kHz in narrowband mode, this > corresponds to a buffer size of 160 samples. Hi Randy, thanks for the reply. So, suppose I encode an audio buffer (8000 kHz, MONO, float) of 640 PCM frames. In output I have 4 speex frame of 20 byte

For example, the following changes are necessary when i convert a Japanese hiragana into katakana in chattr. R code: > chartr("\u3041-\u3093","\u30a1-\u30f3","\u3084\u3063\u305f\u30fc") --- R-alpha.orig/src/main/character.c 2007-09-05 07:13:27.000000000 +0900 +++ R-alpha/src/main/character.c 2007-09-13 16:10:21.000000000 +0900 @@ -2041,6 +2041,16 @@

I have verified that both TLS implementations indeed find the same area of memory. Anything else I could look for? On Tue, Jan 28, 2014 at 4:28 PM, Keno Fischer <kfischer at college.harvard.edu>wrote: > Yes, both JIT code and the native runtime are instrumented. I am under the > impressions that the the C library should guarantee that from the way the > relocations are

>From an example in http://www.uni-muenster.de/ZIV.BennoSueselbeck/s-html/helpfiles/nargs.html , number of arguments in '...' can be obtained by (function(...)nargs())(...) . I now realize that sys.call() doesn't expand '...' when the function is called with '...'. It just returns the call as is. If 'stopifnot' uses sys.call() instead of match.call() , the

How is ccall() implemented? If it manually sets up a stack frame, then it also needs to store argument shadow values in paramtls. I don't think there is an overflow, unless you have a _lot_ of arguments in a function call. On Sun, Feb 2, 2014 at 9:26 AM, Keno Fischer <kfischer at college.harvard.edu> wrote: > Also, I was looking at the instrumented LLVM code and I noticed that the

The one difference I see, is the necessity to pass the dots to the function dotlength : dotlength <- function(...) nargs() myfun <- function(..., someArg = 1){ n1 <- ...length() n2 <- dotlength() n3 <- dotlength(...) return(c(n1, n2, n3)) } myfun(stop("A"), stop("B"), someArg = stop("c")) I don't really see immediately how one can

I would like to suggest a slight modification to diag(). In the case where x is a matrix with both row names and column names the same, it would be reasonable if the resulting vector also had those names. I often use diag() on variance matrices, where this modification is helpful. The modification requires replacing if (is.matrix(x) && nargs() == 1) return(c(x)[1 +

Hi all, enclose a patch to improve the "btrfs subvolume find-new" command. This is a RFC because it is not finished, but it is an usable state and may be discussed. The aim of this patch is: - take in account not only an update of the extent but also an update of the inode and xattr (which includes the acl) - extract the generation reference number directly from a snapshot The new

The code for ccall looks right. Sounds like you have a very small range of instructions where an uninitialized value appear. You could try debugging at asm level. Shadow for b should be passed at offset 0 in __msan_param_tls. MSan could propagate shadow through arithmetic and even some logic operations (like select). It could be that b is clean on function entry, but then something uninitialized